Geology topics

Pete Riley

Publications and source records attributed to Pete Riley.

3 recordsLinked to original sources

USGS2025

Scenario projections of COVID-19 burden in the US, 2024-2025

Importance COVID-19 remains a disease with high burden in the US, prompting continued debate about optimal targets for annual vaccination. Objective To project COVID-19 burden in the US for April 2024 to April 2025 under 6 scenarios of immune escape (20% and 50% per year) and levels of vaccine recommendation (no recommendation, vaccination for individuals at high risk only, vaccination for all eligible groups) and to assess the potential benefit of vaccine recommendations in reducing disease burden. Design, Setting, and Participants For this decision analytical model, the US Scenario Modeling Hub, a collaborative modeling effort, convened 9 teams to provide scenario projections of US COVID-19 hospitalizations and deaths for April 2024 to April 2025, under 6 scenarios combining levels of immune escape and possible vaccine recommendations. Exposure Annually reformulated vaccines were assumed to be 75% effective against hospitalization for variants circulating on June 15, 2024, and available on September 1, 2024. Age- and state-specific coverage was assumed to be as reported in September 2023 to April 2024. Main Outcomes and Measures Ensemble estimates were made for weekly COVID-19 hospitalizations and deaths. Projections are presented for relative and absolute prevented hospitalizations and deaths averted due to vaccination over the April 2024 to April 2025 period. Results For the US population (332 million, with an estimated 58 million aged ≥65 years), COVID-19 was expected to cause 814 000 (95% projection interval [PI], 400 000-1.2 million) hospitalizations and 54 000 (95% PI, 17 000-98 000) deaths for April 2024 to April 2025, comparable in magnitude to the prior year. Vaccination of high-risk groups only was projected to reduce hospitalizations (compared to no vaccination recommendation) by 76 000 (95% CI, 34 000-118 000) and deaths by 7000 (95% CI, 3000-11 000) across both immune escape scenarios. Compared with vaccinating high-risk groups only, a universal vaccine recommendation was projected to provide direct and indirect benefits, further preventing 11 000 hospitalizations and 1000 deaths in those aged 65 years and older. Conclusions and Relevance In this decision analytical modeling study of COVID-19 burden in the US in 2024 to 2025, ensemble projections suggested that although vaccinating high-risk groups had substantial benefits in reducing disease burden, maintaining the vaccine recommendation for all individuals had the potential to save thousands more lives. Despite divergence of projections from observed disease trends in 2024 to 2025—possibly driven by variant emergence patterns and immune escape—averted COVID-19 burden due to vaccination was robust across immune escape scenarios, emphasizing the substantial benefit of broader vaccine availability for all individuals.

JAMA Network Open↗

USGS2017

Extreme geomagnetic storms: Probabilistic forecasts and their uncertainties

Extreme space weather events are low-frequency, high-risk phenomena. Estimating their rates of occurrence, as well as their associated uncertainties, is difficult. In this study, we derive statistical estimates and uncertainties for the occurrence rate of an extreme geomagnetic storm on the scale of the Carrington event (or worse) occurring within the next decade. We model the distribution of events as either a power law or lognormal distribution and use (1) Kolmogorov-Smirnov statistic to estimate goodness of fit, (2) bootstrapping to quantify the uncertainty in the estimates, and (3) likelihood ratio tests to assess whether one distribution is preferred over another. Our best estimate for the probability of another extreme geomagnetic event comparable to the Carrington event occurring within the next 10 years is 10.3% 95% confidence interval (CI) [0.9,18.7] for a power law distribution but only 3.0% 95% CI [0.6,9.0] for a lognormal distribution. However, our results depend crucially on (1) how we define an extreme event, (2) the statistical model used to describe how the events are distributed in intensity, (3) the techniques used to infer the model parameters, and (4) the data and duration used for the analysis. We test a major assumption that the data represent time stationary processes and discuss the implications. If the current trends persist, suggesting that we are entering a period of lower activity, our forecasts may represent upper limits rather than best estimates.

Space Weather↗

USGS2015

On the lognormality of historical magnetic-storm intensity statistics: Implications for extreme-event probabilities

An examination is made of the hypothesis that the statistics of magnetic storm maximum intensities are the realization of a lognormal stochastic process. Weighted least squares and maximum likelihood methods are used to fit lognormal functions to − D s t storm time maxima for years 1957–2012; bootstrap analysis is used to established confidence limits on forecasts. Both methods provide fits that are reasonably consistent with the data; both methods also provide fits that are superior to those that can be made with a power‐law function. In general, the maximum likelihood method provides forecasts having tighter confidence intervals than those provided by weighted least squares. From extrapolation of maximum likelihood fits: a magnetic storm with intensity exceeding that of the 1859 Carrington event, − D s t ≥ 850 nT, occurs about 1.13 times per century and a wide 95% confidence interval of [0.42, 2.41] times per century; a 100 year magnetic storm is identified as having a − D s t ≥ 880 nT (greater than Carrington) but a wide 95% confidence interval of [490, 1187] nT.

Geophysical Research Letters↗